Personal Corporate Survey Chatbot Management

ABSTRACT

Analyzing chatbot/employee dialogs is provided. An analysis of a dialog between a chatbot manager and a plurality of employees regarding a current corporate topic is performed using an artificial intelligence component. Relevant information regarding the current corporate topic is extracted from the dialog based on the analysis. Insights corresponding to the relevant information regarding the current corporate topic are generated using the artificial intelligence component. The relevant information regarding the current corporate topic and the insights are displayed in a dashboard on a client device of a human resource agent.

BACKGROUND 1. Field

The disclosure relates generally to chatbots and more specifically tocapturing mental state and work engagement of employees corresponding toa corporation based on analyzing employee responses captured by aplurality of personal corporate survey chatbots to a question posed by achatbot manager regarding a current corporate topic.

2. Description of the Related Art

A chatbot is a computer program designed to simulate conversation withhuman users, especially via the Internet. Typically, a conversation witha chatbot is a back and forth dialog, such as a person speaks, thechatbot replies, the person responds to the chatbot reply, and so on.The chatbot converts the speech to text, interprets the text's meaning,and responds based on the interpretation. Based on that interpretation,and what the user had previously said, the chatbot knows what to ask orsay to the person. Thus, a chatbot is designed to simulate the way ahuman would behave as a conversational partner.

Chatbots are used in dialog systems for various purposes including, forexample, customer support, request routing, information gathering, andthe like. While some chatbot applications may utilizeword-classification processes, natural language processing, andartificial intelligence, others may simply scan for keywords andgenerate responses using common phrases obtained from an associatedlibrary or database.

SUMMARY

According to one illustrative embodiment, a computer-implemented methodfor analyzing chatbot/employee dialogs is provided. The computerperforms an analysis of a dialog between a chatbot manager and aplurality of employees regarding a current corporate topic using anartificial intelligence component. The computer extracts relevantinformation regarding the current corporate topic from the dialog basedon the analysis. The computer generates insights corresponding to therelevant information regarding the current corporate topic using theartificial intelligence component. The computer displays the relevantinformation regarding the current corporate topic and the insights in adashboard on a client device of a human resource agent.

According to another illustrative embodiment, a computer system foranalyzing chatbot/employee dialogs is provided. The computer systemcomprises a bus system, a storage device storing program instructionsconnected to the bus system, and a processor executing the programinstructions connected to the bus system. The computer system performsan analysis of a dialog between a chatbot manager and a plurality ofemployees regarding a current corporate topic using an artificialintelligence component. The computer system extracts relevantinformation regarding the current corporate topic from the dialog basedon the analysis. The computer system generates insights corresponding tothe relevant information regarding the current corporate topic using theartificial intelligence component. The computer system displays therelevant information regarding the current corporate topic and theinsights in a dashboard on a client device of a human resource agent.

According to another illustrative embodiment, a computer program productfor analyzing chatbot/employee dialogs is provided. The computer programproduct comprises a computer readable storage medium having programinstructions embodied therewith, the program instructions executable bya computer to cause the computer to perform a method. The computerperforms an analysis of a dialog between a chatbot manager and aplurality of employees regarding a current corporate topic using anartificial intelligence component. The computer extracts relevantinformation regarding the current corporate topic from the dialog basedon the analysis. The computer generates insights corresponding to therelevant information regarding the current corporate topic using theartificial intelligence component. The computer displays the relevantinformation regarding the current corporate topic and the insights in adashboard on a client device of a human resource agent.

According to another illustrative embodiment, a method for performingaction steps based on chatbot/employee dialog analysis is provided. Ananalysis of a dialog between a chatbot manager and a plurality ofemployees regarding a current corporate topic is performed using anartificial intelligence component. Relevant information regarding thecurrent corporate topic is extracted from the dialog based on theanalysis. Insights corresponding to the relevant information regardingthe current corporate topic are generated using the artificialintelligence component. A set of action steps controlling a set ofsystems automatically via a set of defined application programminginterfaces is performed based on the relevant information and theinsights.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a pictorial representation of a network of data processingsystems in which illustrative embodiments may be implemented;

FIG. 2 is a diagram of a data processing system in which illustrativeembodiments may be implemented;

FIG. 3 is a diagram illustrating an example of a chatbot managementsystem in accordance with an illustrative embodiment; and

FIGS. 4A-4B are a flowchart illustrating a process for analyzingemployee responses to a question posed by a chatbot manager regarding acurrent corporate topic in accordance with an illustrative embodiment.

DETAILED DESCRIPTION

With reference now to the figures, and in particular, with reference toFIGS. 1-3, diagrams of data processing environments are provided inwhich illustrative embodiments may be implemented. It should beappreciated that FIGS. 1-3 are only meant as examples and are notintended to assert or imply any limitation with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environments may be made.

FIG. 1 depicts a pictorial representation of a network of dataprocessing systems in which illustrative embodiments may be implemented.Network data processing system 100 is a network of computers, dataprocessing systems, and other devices in which the illustrativeembodiments may be implemented. Network data processing system 100contains network 102, which is the medium used to provide communicationslinks between the computers, data processing systems, and other devicesconnected together within network data processing system 100. Network102 may include connections, such as, for example, wire communicationlinks, wireless communication links, fiber optic cables, and the like.

In the depicted example, server 104 and server 106 connect to network102, along with storage 108. Server 104 and server 106 may be, forexample, server computers with high-speed connections to network 102. Inaddition, server 104 and server 106 provide chatbot management servicesto a plurality of client personal corporate survey chatbot devices, eachrespective personal corporate survey chatbot device corresponds to aparticular employee of a corporation that employs a multitude ofemployees, such as, for example, hundreds or thousands of employees. Itshould be noted that the employees may be employed by a different typeof entity, such as, for example, an organization, an agency, aninstitution, an enterprise, a business, a company, or the like, insteadof a corporation. Further, it should be noted that server 104 and server106 may provide chatbot management services to one or more corporationsand/or other entities.

Server 104 and server 106 analyze employee responses, which are capturedby the plurality of client personal corporate survey chatbot devices, toa question posed by a chatbot manager regarding a current corporatetopic to extract relevant information, such as, for example, employeemental state, employee work engagement, employee concerns, employee workenvironment issues, and the like, related to the current corporatetopic. The chatbot manager controls the operation of the plurality ofclient personal corporate survey chatbot devices and resides on server104 and server 106.

Also, it should be noted that server 104 and server 106 may eachrepresent clusters of servers in one or more data centers.Alternatively, server 104 and server 106 may each represent multiplecomputing nodes in one or more cloud environments. Further, server 104and server 106 may provide information, such as, for example, softwareapplications and programs, software updates, software fixes, data files,and the like to client 110, client 112, and client 114.

Client 110, client 112, and client 114 also connect to network 102.Clients 110, 112, and 114 are clients of server 104 and server 106.

In this example, client 110 may be, for example, a desktop or personalcomputer, a laptop computer, a handheld computer, a smart phone, a smarttelevision, or the like, with wire or wireless communication links tonetwork 102. In addition, client 110 may correspond to a human resourceagent of the corporation. The human resource agent may be one of aperson or a software program. The human resource agent may utilizeclient 110 to input a question regarding a current corporate topic intothe chatbot manager of server 104 and server 106. The human resourceagent may also input a chatbot response trigger corresponding to thequestion regarding the current corporate topic into the chatbot manager.The chatbot response trigger initiates an automatic response by thechatbot manager when the trigger is activated by a particular employeeresponse to the question regarding the current corporate topic.Furthermore, the human resource agent may utilize client 110 to receivefeedback and/or a dashboard containing relevant information and insightsgleaned from the employee responses to the question regarding thecurrent corporate topic. The human resource agent may utilize theinformation contained in the feedback and/or dashboard to modify thequestion or create a new question regarding the current corporate topicto collect more relevant information from the employees.

Also in this example, clients 112 and 114 represent the plurality ofclient personal corporate survey chatbot devices, which may have wire orwireless communication links to network 102. The plurality of clientpersonal corporate survey chatbot devices may include, for example,stand-alone devices placed on a desk or workstation of each employee.The plurality of client personal corporate survey chatbot devices mayalso include mobile devices, such as, for example, smartphones, smartwatches, tablets, laptops, and the like, with a chatbot applicationcorresponding to the chatbot management service installed by server 104or server 106 on the mobile devices.

The chatbot manager of server 104 and server 106 utilizes clients 112and 114 (i.e., the plurality of client personal corporate survey chatbotdevices) to present the question regarding the current corporate topicto the employees of the corporation and receive employee responses tothe question. The chatbot manager then analyzes the employee responsesusing a data science system, which includes an artificial intelligencecomponent, to extract the relevant information and generate theinsights, such as, for example, issue description, root cause of theissue, possible solutions to the issue, and the like.

Storage 108 is a network storage device capable of storing any type ofdata in a structured format or an unstructured format. In addition,storage 108 may represent a plurality of network storage devices.Further, storage 108 may store identifiers and network addresses for aplurality of different servers, identifiers and network addresses for aplurality of different client devices, identifiers for a plurality ofdifferent employees, identifiers for human resource agents, identifiersfor a plurality of different chatbot/employee dialogs along withtimestamps and context, and the like. Furthermore, storage 108 may storeother types of data, such as authentication or credential data that mayinclude user names, passwords, and biometric data associated with humanresource agents and system administrators, for example.

In addition, it should be noted that network data processing system 100may include any number of additional server computers, client devices,storage devices, and other devices not shown. Program code located innetwork data processing system 100 may be stored on a computer readablestorage medium and downloaded to a computer or other data processingdevice for use. For example, program code may be stored on a computerreadable storage medium on server 104 and downloaded to client 112 overnetwork 102 for use on client 112.

In the depicted example, network data processing system 100 may beimplemented as a number of different types of communication networks,such as, for example, an internet, an intranet, a local area network(LAN), a wide area network (WAN), a telecommunications network, or anycombination thereof. FIG. 1 is intended as an example only, and not asan architectural limitation for the different illustrative embodiments.

As used herein, when used with reference to items, “a number of” meansone or more of the items. For example, “a number of different types ofcommunication networks” is one or more different types of communicationnetworks. Similarly, “a set of,” when used with reference to items,means one or more of the items.

Further, the term “at least one of,” when used with a list of items,means different combinations of one or more of the listed items may beused, and only one of each item in the list may be needed. In otherwords, “at least one of” means any combination of items and number ofitems may be used from the list, but not all of the items in the listare required. The item may be a particular object, a thing, or acategory.

For example, without limitation, “at least one of item A, item B, oritem C” may include item A, item A and item B, or item B. This examplemay also include item A, item B, and item C or item B and item C. Ofcourse, any combinations of these items may be present. In someillustrative examples, “at least one of” may be, for example, withoutlimitation, two of item A; one of item B; and ten of item C; four ofitem B and seven of item C; or other suitable combinations.

With reference now to FIG. 2, a diagram of a data processing system isdepicted in accordance with an illustrative embodiment. Data processingsystem 200 is an example of a computer, such as server 104 in FIG. 1, inwhich computer readable program code or instructions implementingchatbot management processes of illustrative embodiments may be located.In this example, data processing system 200 includes communicationsfabric 202, which provides communications between processor unit 204,memory 206, persistent storage 208, communications unit 210,input/output (I/O) unit 212, and display 214.

Processor unit 204 serves to execute instructions for softwareapplications and programs that may be loaded into memory 206. Processorunit 204 may be a set of one or more hardware processor devices or maybe a multi-core processor, depending on the particular implementation.

Memory 206 and persistent storage 208 are examples of storage devices216. As used herein, a computer readable storage device or computerreadable storage medium is any piece of hardware that is capable ofstoring information, such as, for example, without limitation, data,computer readable program instructions in functional form, and/or othersuitable information either on a transient basis or a persistent basis.Further, a computer readable storage device or computer readable storagemedium excludes a propagation medium, such as a transitory signal.Memory 206, in these examples, may be, for example, a random-accessmemory (RAM), or any other suitable volatile or non-volatile storagedevice, such as a flash memory. Persistent storage 208 may take variousforms, depending on the particular implementation. For example,persistent storage 208 may contain one or more devices. For example,persistent storage 208 may be a disk drive, a solid-state drive, arewritable optical disk, a rewritable magnetic tape, or some combinationof the above. The media used by persistent storage 208 may be removable.For example, a removable hard drive may be used for persistent storage208.

In this example, persistent storage 208 stores chatbot manager 218.However, it should be noted that even though chatbot manager 218 isillustrated as residing in persistent storage 208, in an alternativeillustrative embodiment chatbot manager 218 may be a separate componentof data processing system 200. For example, chatbot manager 218 may be ahardware component coupled to communication fabric 202 or a combinationof hardware and software components. In another alternative illustrativeembodiment, a first set of components of chatbot manager 218 may belocated in data processing system 200 and a second set of components ofchatbot manager 218 (e.g., data science system) may be located in asecond data processing system, such as, for example, server 106 in FIG.1.

Chatbot manager 218 controls the process of analyzing employee responsescaptured by a plurality of personal corporate survey chatbots to aquestion regarding a current corporate topic to extract relevantinformation, such as employee mental state, employee work engagement,employee concerns, work environment issues, and the like, and generateinsights, such as issue description, issue root cause, possiblesolutions to the root cause, and the like, from the employee responses.In this example, chatbot manager 218 includes artificial intelligencemanager 220. Alternatively, artificial intelligence manager 220 may beincluded in a data science system, which may be a separate component ofdata processing system 200.

Personal corporate survey chatbots 222 represent identifiers for aplurality of client personal corporate survey chatbot devices, such as,for example, clients 112 and 114 in FIG. 1, which are clients of chatbotmanager 218. Employees 224 represent identifiers for a plurality ofemployees employed by corporation 226. Each respective employee inemployees 224 corresponds to a particular personal corporate surveychatbot in personal corporate survey chatbots 222. Corporation 226represents an identifier of the corporation, which may be any type ofcorporation or entity.

Human resource agent 228 represents an identifier of a particular personin the human resources department of corporation 226. However, it shouldbe noted that human resource agent 228 may not be a person, but insteadmay be a human resource software program. Human resource agent 228creates question 230 regarding topic 232. Topic 232 may be any currentcorporate topic, subject, matter, issue, area, focus, or the like. Forexample, topic 232 may be, for example, a current renovation project ofcorporation 226. Thus, question 230 for this example may be, “How do youlike the current renovation project?” Employee responses 234 representanswers provided by employees 224 to question 230 regarding topic 232.An employee response may be, for example, “I like the renovations.”Chatbot manager 218 utilizes personal corporate survey chatbots 222 topose question 230 to employees 224 and collect employee responses 234.

Human resource agent 228 also creates chatbot response trigger 236.Chatbot response trigger 236 causes an automatic response to particularresponses provided by one or more employees to question 230 regardingtopic 232. In other words, chatbot response trigger 236 specificallyrelates to topic 232.

Dialog 238 represents a dialog identifier of the conversation betweenchatbot manager 218 and employees 224 and includes question 230 and allemployee responses 234. Dialog 238 may also include other information,such as, for example, dialog timestamps corresponding to when question230 was presented and when each employee response was received, alongwith any dialog context (e.g., geolocation, setting, situation,circumstance, environment, or the like) associated with theconversation. Chatbot manager 218 stores dialog 238 in a dialog databaseor storage, such as, for example, storage 108 in FIG. 1.

Chatbot manager 218 utilizes artificial intelligence component 220 toanalyze dialog 238 and extract relevant information 240 and generateinsights 242. Relevant information 240 is any information related totopic 232 that artificial intelligence component 220 determines to bepertinent, significant, important, or the like. Relevant information 240may include, for example, employee sentiment, employee concern, employeeengagement, work environment issues or problems, employee conflict, orthe like, related to topic 232. Insights 242 represent understanding orvalue obtained or gained through the use of machine learning analyticsby artificial intelligence component 220. Insights 242 may include, forexample, root cause for a particular employee sentiment or workenvironment issue and a possible solution to the root cause. Chatbotmanager 218 displays relevant information 240 and insights 242 indashboard 244. Dashboard 244 is an improved graphical user interfacethat allows human resource agent 228 to quickly identify any issuesneeding to be addressed, along with any possible solutions.

Moreover, chatbot manager 218 may automatically perform a set of actionsteps based on the extracted relevant information and generatedinsights. The set of action steps may include, for example, chatbotmanager 218 automatically connecting to and controlling a set of one ormore other or external systems of the corporation using a set of definedapplication programming interfaces. For example, chatbot manager 218 mayautomatically control a heating, ventilation, and air conditioningsystem of a building corresponding to the corporation to automaticallyadjust a temperature in the building or in one or more specific rooms ofthe building in response to identifying a temperature issue in one ormore employee responses complaining about the current temperature oftheir work environment. As another example, chatbot manager 218 mayautomatically control a security system of the building to automaticallylock doors to the building or one or more specific doors in the buildingin response to identifying a security issue in one or more employeeresponses indicating fear due to a possible threat in their workenvironment. Further, chatbot manager 218 may automatically control acommunication system of the building to automatically contact corporatesecurity and/or the police department in response to identifying thesecurity issue. As a further example, chatbot manager 218 mayautomatically control a fire suppression system of the building toautomatically start fire suppression in the building or in one or morespecific rooms of the building in response to identifying a fire issuein one or more employee responses indicating intense heat levels, heavyamounts of smoke, and/or fire in their work environment. Furthermore,chatbot manager 218 may automatically control the communication systemto automatically contact the fire department in response to identifyingthe fire issue. Moreover, chatbot manager 218 may use the communicationsystem to automatically contact medical professionals in response toidentifying a medical issue in one or more employee responses indicatinginjury, shortness of breath, or the like.

As a result, data processing system 200 operates as a special purposecomputer system in which chatbot manager 218 in data processing system200 enables analysis of employee responses 234 captured by personalcorporate survey chatbots 222 to question 230 regarding currentcorporate topic 232 to extract relevant information 240 (e.g., employeemental state, employee work engagement, employee concerns, workenvironment issues, and the like) and generate insights 242 (e.g., issuedescription, root cause, possible solutions, and the like) from employeeresponses 234. In particular, chatbot manager 218 transforms dataprocessing system 200 into a special purpose computer system as comparedto currently available general computer systems that do not have chatbotmanager 218.

Communications unit 210, in this example, provides for communicationwith other computers, data processing systems, and devices via anetwork, such as network 102 in FIG. 1. Communications unit 210 mayprovide communications through the use of both physical and wirelesscommunications links. The physical communications link may utilize, forexample, a wire, cable, universal serial bus, or any other physicaltechnology to establish a physical communications link for dataprocessing system 200. The wireless communications link may utilize, forexample, shortwave, high frequency, ultrahigh frequency, microwave,wireless fidelity (Wi-Fi), Bluetooth® technology, global system formobile communications (GSM), code division multiple access (CDMA),second-generation (2G), third-generation (3G), fourth-generation (4G),4G Long Term Evolution (LTE), LTE Advanced, fifth-generation (5G), orany other wireless communication technology or standard to establish awireless communications link for data processing system 200.

Input/output unit 212 allows for the input and output of data with otherdevices that may be connected to data processing system 200. Forexample, input/output unit 212 may provide a connection for user inputthrough a keypad, a keyboard, a mouse, a microphone, and/or some othersuitable input device. Display 214 provides a mechanism to displayinformation to a user and may include touch screen capabilities to allowthe user to make on-screen selections through user interfaces or inputdata, for example.

Instructions for the operating system, applications, and/or programs maybe located in storage devices 216, which are in communication withprocessor unit 204 through communications fabric 202. In thisillustrative example, the instructions are in a functional form onpersistent storage 208. These instructions may be loaded into memory 206for running by processor unit 204. The processes of the differentembodiments may be performed by processor unit 204 usingcomputer-implemented instructions, which may be located in a memory,such as memory 206. These program instructions are referred to asprogram code, computer usable program code, or computer readable programcode that may be read and run by a processor in processor unit 204. Theprogram instructions, in the different embodiments, may be embodied ondifferent physical computer readable storage devices, such as memory 206or persistent storage 208.

Program code 246 is located in a functional form on computer readablemedia 248 that is selectively removable and may be loaded onto ortransferred to data processing system 200 for running by processor unit204. Program code 246 and computer readable media 248 form computerprogram product 250. In one example, computer readable media 248 may becomputer readable storage media 252 or computer readable signal media254.

In these illustrative examples, computer readable storage media 252 is aphysical or tangible storage device used to store program code 246rather than a medium that propagates or transmits program code 246. Inother words, computer readable storage media 252 exclude a propagationmedium, such as transitory signals. Computer readable storage media 252may include, for example, an optical or magnetic disc that is insertedor placed into a drive or other device that is part of persistentstorage 208 for transfer onto a storage device, such as a hard drive,that is part of persistent storage 208. Computer readable storage media252 also may take the form of a persistent storage, such as a harddrive, a thumb drive, or a flash memory that is connected to dataprocessing system 200.

Alternatively, program code 246 may be transferred to data processingsystem 200 using computer readable signal media 254. Computer readablesignal media 254 may be, for example, a propagated data signalcontaining program code 246. For example, computer readable signal media254 may be an electromagnetic signal, an optical signal, or any othersuitable type of signal. These signals may be transmitted overcommunication links, such as wireless communication links, an opticalfiber cable, a coaxial cable, a wire, or any other suitable type ofcommunications link.

Further, as used herein, “computer readable media 248” can be singularor plural. For example, program code 246 can be located in computerreadable media 248 in the form of a single storage device or system. Inanother example, program code 246 can be located in computer readablemedia 248 that is distributed in multiple data processing systems. Inother words, some instructions in program code 246 can be located in onedata processing system while other instructions in program code 246 canbe located in one or more other data processing systems. For example, aportion of program code 246 can be located in computer readable media248 in a server computer while another portion of program code 246 canbe located in computer readable media 248 located in a set of clientcomputers.

The different components illustrated for data processing system 200 arenot meant to provide architectural limitations to the manner in whichdifferent embodiments can be implemented. In some illustrative examples,one or more of the components may be incorporated in or otherwise form aportion of, another component. For example, memory 206, or portionsthereof, may be incorporated in processor unit 204 in some illustrativeexamples. The different illustrative embodiments can be implemented in adata processing system including components in addition to or in placeof those illustrated for data processing system 200. Other componentsshown in FIG. 2 can be varied from the illustrative examples shown. Thedifferent embodiments can be implemented using any hardware device orsystem capable of running program code 246.

In the illustrative examples, the hardware may take a form selected fromat least one of a circuit system, an integrated circuit, an applicationspecific integrated circuit (ASIC), a programmable logic device, or someother suitable type of hardware configured to perform a number ofoperations. With a programmable logic device, the device may beconfigured to perform the number of operations. The device may bereconfigured at a later time or may be permanently configured to performthe number of operations. Programmable logic devices include, forexample, a programmable logic array, a programmable array logic, a fieldprogrammable logic array, a field programmable gate array, and othersuitable hardware devices. Additionally, the processes may beimplemented in organic components integrated with inorganic componentsand may be comprised entirely of organic components excluding a humanbeing. For example, the processes may be implemented as circuits inorganic semiconductors.

In another example, a bus system may be used to implement communicationsfabric 202 and may be comprised of one or more buses, such as a systembus or an input/output bus. Of course, the bus system may be implementedusing any suitable type of architecture that provides for a transfer ofdata between different components or devices attached to the bus system.

Corporations are finding it difficult to collect information fromemployees on a daily basis regarding topics, such as, for example,distracting noises in the work environment, cleanliness of the workenvironment, temperature of the work environment, and the like, whichare not included in formal corporate employee engagement pulse surveys.Employee engagement is a fundamental concept in an effort to understandand describe, both qualitatively and quantitatively, the nature of therelationship between a corporation and its employees. An engagedemployee is one who is enthusiastic about assigned work and takespositive action to further the corporation's interests. In contrast, adisengaged employee may be someone doing the bare minimum on assignedwork (a.k.a., “coasting”) or who is actively seeking to damage thecorporation's reputation. If the mental state and concerns of employeesregarding different topics, which are not included in formal corporateemployee engagement pulse surveys, are not identified or identified toolate, then employee engagement and performance may be negativelyimpacted, along with results of the formal corporate employee engagementpulse surveys.

Through interactions of employees with personal corporate surveychatbots, illustrative embodiments using a chatbot manager can capture,for example, the mental state (e.g., frame of mind, thoughts, opinions,viewpoints, attitudes, sentiment, and the like) of employees, possiblework environment issues or problems experienced by employees, employeeconcerns, employee engagement with assigned work, and the like, withinthe corporation. The chatbot manager acts automatically in directingdialogs with the employees and generates a database of these dialogs.

Illustrative embodiments utilize a plurality of personal corporatesurvey chatbots that engages employees in direct dialog to collectinformation regarding one or more topics, such as, for example, theircurrent mental state, active issues or concerns, level of workengagement, and the like. Analyzing this collected information from thedialogs, illustrative embodiments can generate possible solutions toaddress employee issues or concerns and improve or adjust resources,such as, for example, employee work environment, to improve employeemental state and engagement. Illustrative embodiments store the dialogsgenerated by the interactions between the personal corporate surveychatbots and employees within a database so that illustrativeembodiments can extract relevant information regarding the dialogtopics. Illustrative embodiments utilize a data science system toextract the relevant information. Data science is an inter-disciplinaryfield that uses scientific methods, processes, and algorithms to extractrelevant information from structured and unstructured data.

After illustrative embodiments analyze this extracted information,illustrative embodiments can then generate insights into this extractedinformation, which may reveal, for example, corporate personnel issues,corporate opportunities for improvement, employee work environmentproblems, and the like. Upon identifying and classifying issues andopportunities, illustrative embodiments present the extracted relevantinformation and generated insights within a dashboard with specificalerts to appropriate corporate personnel (e.g., human resourcemanagers, corporate executives, and the like). The internal corporatecommunications may be based on any messaging service owned by thecorporation or operated by a third-party entity (e.g., Cisco Webex,Windows Live Messenger, Slack, or the like). Thus, illustrativeembodiments, using the chatbot manager, are capable of automatically, ona day-by-day basis, capturing employee mental state, acquiring employeework engagement levels, communicating directly in real-time withemployees regarding different topics not on formal surveys, developinginsights into relevant information extracted from the chatbot/employeedialogs, and the like.

As an exemplary use case scenario, a corporation recently completed arenovation of the employee work environment. Human resource personnelwant to know the employees' mental state (e.g., sentiment, perception,attitude, viewpoint, or the like) regarding the renovation. The personalcorporate survey chatbots contact corresponding employees impacted bythe renovation at a random time, for example. The chatbot may initiatethe dialog with asking a question, such as, for example: “Good morning,how are you?”; “Hello, how is your work environment after therenovation?”; “Good morning, how can your work environment be improvedtoday?”; “Hello, are you happy with your current work environment and,if not, why?”; or the like.

Based on employee responses to the question posed by the personalcorporate survey chatbots to the employees, the chatbot manager using anartificial intelligence component identifies, for example, acommunication pattern, such as a common issue expressed in employeeresponses, and seeks to determine a root cause of the issue. Forexample, an employee may have responded to the chatbot's question with“Today I am very angry because, when I arrived, my work station wascovered with dust. Dust was even in my coffee cup.” As a result, thechatbot manager may initially determine that the dust issue is a resultof the renovation. The chatbot stores this relevant information in thedatabase and presents this relevant information and insights within adashboard display in real-time to appropriate human resource personnel.Assume that several other employees reported this same issue of dust tothe personal corporate survey chatbots, which indicates an issue thatthe corporation needs to address. After initially determining a possibleroot cause of the dust (e.g., the renovation), the chatbot managercontinues to ask more open questions until the chatbot manager candetermine that the root cause of the dust was actually the renovationwith a level of certainty above a threshold level of certainty, such as,for example, 75%, 80%, 85%, 90%, or 95% level of certainty.

As another exemplary use case scenario, the chatbot contacts employeesevery day at random and at random times and asks some open questionsregarding the corporation's formal employee engagement pulse surveys.Based on employee responses, the chatbot manager continues to askquestions in order to identify, for example, an issue and searches todetermine the root cause of the issue. However, if an employee has nointerest in delving into the topic, the chatbot manager stores thecaptured dialog as satisfaction survey data and presents the data withinthe dashboard as the same. An example of this chatbot/employee dialogmay be: 1) Chatbot, “Good morning, how are you feeling today? Very sad,sad, neutral, happy, or very happy?”; 2) Employee, “Very sad.”; 3)Chatbot, “How can I help you to feel better?”; 4) Employee, “You can't,it's personal.”; and 5) Chatbot, “Okay, I hope things get better. Have anice day.”

A human resource agent starts the process by inputting a set ofquestions regarding a set of topics, on a periodic basis or at random,into the chatbot manager, along with a set of chatbot response triggerscorresponding to the set of questions. The chatbot manager, via anetwork, sends or pushes the set of questions to the plurality ofpersonal corporate survey chatbots, each personal corporate surveychatbot in the plurality of personal corporate survey chatbotscorresponds to a respective employee of the corporation. The pluralityof personal corporate survey chatbots captures employee responses to theset of questions for pre-processing in a data science system of thechatbot manager. For example, questions posed by the plurality ofpersonal corporate survey chatbots are answered by employees withstatements that are preprocessed in the data science system of thechatbot manager to extract relevant information regarding the set oftopics. Based on a set of chatbot response triggers or rules defined bythe human resource agent, chatbot manager responses are triggeredaccording to the statements made by the employees revealing, forexample, the mental state of employees, work engagement of employees,issues or problems described by employees, concerns of employees, andthe like. As a result, the dialog between a particular employee and acorresponding personal corporate survey chatbot may include any type ofdialog based on defined chatbot response triggers.

Thus, illustrative embodiments provide one or more technical solutionsthat overcome a technical problem with chatbot/employee dialog analysisand interpretation. As a result, these one or more technical solutionsprovide a technical effect and practical application in the field ofchatbots.

With reference now to FIG. 3, a diagram illustrating an example of achatbot management system is depicted in accordance with an illustrativeembodiment. Chatbot management system 300 may be implemented in anetwork of data processing systems, such as network data processingsystem 100 in FIG. 1. Chatbot management system 300 is a system ofhardware and software components for capturing mental state and workengagement of employees corresponding to a corporation based onanalyzing employee responses captured by a plurality of personalcorporate survey chatbots to a question posed by a chatbot managerregarding a current corporate topic.

In this example, chatbot management system 300 includes server 302,client device 304, and personal corporate survey chatbots 306. Server302, client device 304, and personal corporate survey chatbots 306 maybe, for example, server 104, client 110, and clients 112 and 114 in FIG.1, respectively. However, it should be noted that chatbot managementsystem 300 is intended as an example only and not as a limitation onillustrative embodiments. In other words, chatbot management system 300may include any number of servers, clients, and personal corporatesurvey chatbots.

In this example, server 302 includes chatbot manager 308, such as, forexample, chatbot manager 218 in FIG. 2, and data science system 310.Data science system 310 includes storage component 312 and artificialintelligence component 314.

Storage component 312 is storage for chatbot/employee dialogs and may bea traditional database. Storage component 312 stores the dialogs, alongwith other information, such as timestamps corresponding to the dialogs,context of the dialogs, who designed the questions (i.e., human resourceagent identifier), who responded to the questions (i.e., employeeidentifiers), and the like. Also, it should be noted that storagecomponent 312 may store the dialog information in a structured or anunstructured format.

Artificial intelligence component 314 may utilize machine learning toperform various analyses, such as, for example, speech recognition,speech-to-text conversion, natural language processing, patternrecognition, data statistics analysis, sentiment analysis, anomalydetection, question and answer classification, root cause analysis, andthe like. Artificial intelligence component 314 may also provide levelsof anonymization to collected employee responses for employee privacyand security. Artificial intelligence component 314 provides the basisfor the general operation of chatbot manager 308 and contains generalrules for the operation, along with knowledge engineering techniques andlogical reasoning (e.g., deductive, inductive, and abductive reasoning)to generate relevant information and insights. Output of artificialintelligence component 314 may be, for example, structured dialogs, withcorresponding classifications, sentiments, targets, contexts, and thelike.

Chatbot manager 308 receives a flow of questions and chatbot responsetriggers from human resource agent 316 via client device 304 as input318. Human resource agent 316 may create the flow of questions asoriginal questions or as variants of answers recently provided byemployees to help identify root causes of work environment issues ordetermine possible solutions to employee concerns, for example. Humanresource agent 316 may define triggers or rules for chatbot manager 308responses according to spontaneous manifestations or according toemployee responses during current dialogs. For example, in the event anew work task is assigned to a set of employees, human resource agent316 can proactively define a chatbot response explaining details of thenew task and deadlines associated with the work. As another example, inthe event an employee answers chatbot manager 308 posed questionsregarding different topics with a particular sentiment (e.g., anger)over a certain period of time, human resource agent 316 can proactivelystart a specific set of questions regarding workplace satisfaction forthat particular employee, which may provide human resource agent 316with preventive information (e.g., how to resolve the employee's angerbefore a situation or issue arises). Chatbot manager 308 stores the flowof questions and chatbot response triggers in storage component 312.

Chatbot manager 308 presents question 320 to employee 322 via personalcorporate survey chatbots 306. Question 320 may be any type of questioncorresponding to a current corporate topic, such as, topic 232 in FIG.2. Personal corporate survey chatbots 306 receive responses 324 toquestion 320 from employee 322 and transmit responses 324 to chatbotmanager 308. In addition, chatbot manager 308 may utilize a questionanswering system to answer questions posed by one or more employees inresponses 324. Further, employees 322 may provide suggestions forimprovements, compliments regarding changes, or the like in responses324.

Chatbot manager 308 stores employee responses 324, along with question320, in storage component 312 as dialog 326. In addition to employeeresponses 324 and question 320, dialog 326 includes identifier 328,timestamps 330, and context 332. Chatbot manager 308 sends dialog 326 toartificial intelligence component 314 for analysis.

Artificial intelligence component 314 analyzes dialog 326 to extractrelevant information 334 corresponding to the current corporate topic.Relevant information 334 may include, for example, current mental stateof employees (e.g., how they are feeling), targets (e.g., otheremployees) of the dialog, work environment issues, employee engagementwith assigned work-related tasks, employee concerns, and the like.Artificial intelligence component 314 summarizes relevant information334 in a report and sends the report to chatbot manager 308. Chatbotmanager 308 then sends the summary report to human resource agent 316via client device 304 as feedback 336. Human resource agent 316 mayutilize feedback 336 to modify previously asked questions or to developnew questions in an effort to continue to collect relevant informationor higher quality information from employees 322 regarding the currentcorporate topic.

Furthermore, artificial intelligence component 314 can execute chatbotresponse triggers defined by human resource agent 316 based on employeeresponses 324. For example, based on a current renovation job in anemployee breakroom (i.e., the current corporate topic), human resourceagent 316 may define a chatbot response trigger for when a receivedemployee response contains negative sentiment regarding cleanliness ofthe breakroom due to the renovation. Upon activation of the chatbotresponse trigger by the negative sentiment expressed in the employeeresponse, the chatbot response trigger automatically sends a reply tothat employee stating, for example, “Sorry for the inconvenience, thebreakroom renovation is set to finish on Friday.”

Moreover, artificial intelligence component 314 generates insights 338based on relevant information 334 extracted from dialog 326 regardingthe current corporate topic. Insights 338 may include, for example, rootcause of any issue, sentiment, concern, complaint, or problem and one ormore possible solutions to the root cause. Insights 338 may also includestatistics, highlights, alerts, and the like. Chatbot manager 308 placesrelevant information 334 and insights 338 in dashboard 340.

Dashboard 340 is a graphical user interface that renders relevantinformation 334 and insights 338 on client device 304. Dashboard 340structures and displays relevant information 334 and insights 338 foreasier review and understanding by human resource agent 316.

With reference now to FIGS. 4A-4B, a flowchart illustrating a processfor analyzing employee responses to a question posed by a chatbotmanager regarding a current corporate topic is shown in accordance withan illustrative embodiment. The process shown in FIGS. 4A-4B may beimplemented in a computer, such as, for example, server 104 in FIG. 1 ordata processing system 200 in FIG. 2. For example, the process can beimplemented in chatbot manager 218 in FIG. 2.

The process begins when the computer, using the chatbot manager,receives a question regarding a current corporate topic, along with achatbot response trigger corresponding to the question, from a clientdevice of a human resource agent corresponding to a corporation via anetwork (step 402). The computer, using the chatbot manager, sends thequestion regarding the current corporate topic via the network to aplurality of personal corporate survey chatbots corresponding toemployees of the corporation to start a dialog regarding the currentcorporate topic (step 404). The computer, using the chatbot manager,receives responses to the question regarding the current corporate topicfrom the employees via the plurality of personal corporate surveychatbots over the network (step 406).

The computer, using the chatbot manager, makes a determination as towhether one or more of the responses activate the chatbot responsetrigger corresponding to the question (step 408). If the computer, usingthe chatbot manager, determines that none of the responses activate thechatbot response trigger corresponding to the question, no output ofstep 408, then the process proceeds to step 414. If the computer, usingthe chatbot manager, determines that one or more of the responsesactivate the chatbot response trigger corresponding to the question, yesoutput of step 408, then the computer, using the chatbot manager, sendsa chatbot response via the network to one or more personal corporatesurvey chatbots corresponding to one or more employees providing the oneor more responses activating the chatbot response trigger for thechatbot response (step 410).

In addition, the computer, using the chatbot manager, makes adetermination as to whether the chatbot response contains a questionregarding the one or more responses activating the chatbot responsetrigger (step 412). If the computer, using the chatbot manager,determines that the chatbot response does contain a question regardingthe one or more responses activating the chatbot response trigger, yesoutput of step 412, then the process returns to step 406 where thecomputer receives responses to the question from the one or moreemployees providing the one or more responses activating the chatbotresponse trigger. If the computer, using the chatbot manager, determinesthat the chatbot response does not contain a question regarding the oneor more responses activating the chatbot response trigger, no output ofstep 412, then the computer, using the chatbot manager, stores allemployee responses as the dialog regarding the current corporate topicin a dialog database (step 414).

Further, the computer, using the chatbot manager, performs an analysisof the dialog regarding the current corporate topic using an artificialintelligence component of a data science system of the chatbot manager(step 416). Furthermore, the computer, using the chatbot manager,extracts relevant information regarding the current corporate topic fromthe dialog based on the analysis (step 418). Moreover, the computer,using the chatbot manager, generates insights corresponding to therelevant information regarding the current corporate topic using theartificial intelligence component (step 420).

The computer, using the chatbot manager, displays the relevantinformation regarding the current corporate topic and the insights in adashboard on a display of the client device of the human resource agent(step 422). The computer, using the chatbot manager, makes adetermination as to whether a follow up question regarding the currentcorporate topic was received from the human resource agent afterreviewing the relevant information and insights in the dashboard (step424). If the computer, using the chatbot manager, determines that afollow up question regarding the current corporate topic was receivedfrom the human resource agent after reviewing the relevant informationand insights in the dashboard, yes output of step 424, then the processreturns to step 404 where the computer, using the chatbot manager, sendsthe follow up question via the network to the plurality of personalcorporate survey chatbots corresponding to the employees. If thecomputer, using the chatbot manager, determines that a follow upquestion regarding the current corporate topic was not received from thehuman resource agent after reviewing the relevant information andinsights in the dashboard, no output of step 424, then the processterminates thereafter.

The flowcharts and block diagrams in the different depicted embodimentsillustrate the architecture, functionality, and operation of somepossible implementations of apparatuses and methods in an illustrativeembodiment. In this regard, each block in the flowcharts or blockdiagrams can represent at least one of a module, a segment, a function,or a portion of an operation or step. For example, one or more of theblocks can be implemented as program code, hardware, or a combination ofthe program code and hardware. When implemented in hardware, thehardware may, for example, take the form of integrated circuits that aremanufactured or configured to perform one or more operations in theflowcharts or block diagrams. When implemented as a combination ofprogram code and hardware, the implementation may take the form offirmware. Each block in the flowcharts or the block diagrams may beimplemented using special purpose hardware systems that perform thedifferent operations or combinations of special purpose hardware andprogram code run by the special purpose hardware.

In some alternative implementations of an illustrative embodiment, thefunction or functions noted in the blocks may occur out of the ordernoted in the figures. For example, in some cases, two blocks shown insuccession may be performed substantially concurrently, or the blocksmay sometimes be performed in the reverse order, depending upon thefunctionality involved. Also, other blocks may be added in addition tothe illustrated blocks in a flowchart or block diagram.

Thus, illustrative embodiments of the present invention provide acomputer-implemented method, computer system, and computer programproduct for analyzing employee responses captured by a plurality ofpersonal corporate survey chatbots to a question regarding a currentcorporate topic to extract relevant information, such as employee mentalstate, employee work engagement, employee concerns, work environmentissues, and the like, and generate insights, such as issue root cause,possible solutions to the root cause, and the like, from the employeeresponses. The descriptions of the various embodiments of the presentinvention have been presented for purposes of illustration, but are notintended to be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method for analyzingchatbot/employee dialogs, the computer-implemented method comprising:performing, by a computer, an analysis of a dialog between a chatbotmanager and a plurality of employees regarding a current corporate topicusing an artificial intelligence component; extracting, by the computer,relevant information regarding the current corporate topic from thedialog based on the analysis; generating, by the computer, insightscorresponding to the relevant information regarding the currentcorporate topic using the artificial intelligence component; anddisplaying, by the computer, the relevant information regarding thecurrent corporate topic and the insights in a dashboard on a clientdevice of a human resource agent.
 2. The computer-implemented method ofclaim 1 further comprising: receiving, by the computer, a questionregarding the current corporate topic, along with a chatbot responsetrigger corresponding to the question, from the client device of thehuman resource agent via a network; sending, by the computer, using thechatbot manager, the question regarding the current corporate topic viathe network to a plurality of personal corporate survey chatbotscorresponding to the plurality of employees to start the dialog betweenthe chatbot manager and the plurality of employees regarding the currentcorporate topic; and receiving, by the computer, using the chatbotmanager, responses to the question regarding the current corporate topicfrom the plurality of employees via the plurality of personal corporatesurvey chatbots over the network.
 3. The computer-implemented method ofclaim 2 further comprising: determining, by the computer, whether one ormore of the responses activate the chatbot response triggercorresponding to the question, wherein the chatbot response triggerinitiates an automatic response by the chatbot manager when the chatbotresponse trigger is activated by a particular employee response to thequestion regarding the current corporate topic; and responsive to thecomputer determining that one or more of the responses activate thechatbot response trigger corresponding to the question, sending, by thecomputer, a chatbot response via the network to one or more personalcorporate survey chatbots corresponding to one or more employeesproviding the one or more of the responses activating the chatbotresponse trigger for the chatbot response.
 4. The computer-implementedmethod of claim 3 further comprising: determining, by the computer,whether the chatbot response contains a question regarding the one ormore of the responses activating the chatbot response trigger; andresponsive to the computer determining that the chatbot responsecontains a question regarding the one or more of the responsesactivating the chatbot response trigger, receiving, by the computer,responses to the question regarding the one or more of the responsesfrom the one or more employees providing the one or more of theresponses activating the chatbot response trigger.
 5. Thecomputer-implemented method of claim 4 further comprising: storing, bythe computer, all employee responses as the dialog between the chatbotmanager and the plurality of employees regarding the current corporatetopic in a dialog database, wherein the dialog includes the question,all of the employee responses, dialog identifier, dialog timestamps, anddialog context.
 6. The computer-implemented method of claim 1 furthercomprising: determining, by the computer, whether a follow up questionregarding the current corporate topic was received from the humanresource agent after reviewing the relevant information and the insightsin the dashboard; and responsive to the computer determining that afollow up question regarding the current corporate topic was receivedfrom the human resource agent after reviewing the relevant informationand the insights in the dashboard, sending, by the computer, the followup question via a network to a plurality of personal corporate surveychatbots corresponding to the plurality of employees.
 7. Thecomputer-implemented method of claim 1 further comprising: performing,by the computer, using the chatbot manager, a set of action stepsautomatically based on the relevant information and the insights byconnecting to and controlling a set of other systems via a set ofdefined application programming interfaces.
 8. The computer-implementedmethod of claim 1, wherein the relevant information is at least one ofemployee mental state, employee work engagement, employee concerns, andemployee work environment issues related to the current corporate topic.9. The computer-implemented method of claim 1, wherein the insights areat least one of description of an issue, root cause of the issue, andpossible solutions to the issue.
 10. The computer-implemented method ofclaim 1, wherein the dashboard is a graphical user interface that allowsthe human resource agent to quickly identify any issues needing to beaddressed along with any possible solutions.
 11. Thecomputer-implemented method of claim 1, wherein the human resource agentis a software program.
 12. A computer system for analyzingchatbot/employee dialogs, the computer system comprising: a bus system;a storage device connected to the bus system, wherein the storage devicestores program instructions; and a processor connected to the bussystem, wherein the processor executes the program instructions to:perform an analysis of a dialog between a chatbot manager and aplurality of employees regarding a current corporate topic using anartificial intelligence component; extract relevant informationregarding the current corporate topic from the dialog based on theanalysis; generate insights corresponding to the relevant informationregarding the current corporate topic using the artificial intelligencecomponent; and display the relevant information regarding the currentcorporate topic and the insights in a dashboard on a client device of ahuman resource agent.
 13. The computer system of claim 12, wherein theprocessor further executes the program instructions to: receive aquestion regarding the current corporate topic, along with a chatbotresponse trigger corresponding to the question, from the client deviceof the human resource agent via a network; send, using the chatbotmanager, the question regarding the current corporate topic via thenetwork to a plurality of personal corporate survey chatbotscorresponding to the plurality of employees to start the dialog betweenthe chatbot manager and the plurality of employees regarding the currentcorporate topic; and receive, using the chatbot manager, responses tothe question regarding the current corporate topic from the plurality ofemployees via the plurality of personal corporate survey chatbots overthe network.
 14. The computer system of claim 13, wherein the processorfurther executes the program instructions to: determine whether one ormore of the responses activate the chatbot response triggercorresponding to the question, wherein the chatbot response triggerinitiates an automatic response by the chatbot manager when the chatbotresponse trigger is activated by a particular employee response to thequestion regarding the current corporate topic; and send a chatbotresponse via the network to one or more personal corporate surveychatbots corresponding to one or more employees providing the one ormore of the responses activating the chatbot response trigger for thechatbot response in response to determining that one or more of theresponses activate the chatbot response trigger corresponding to thequestion.
 15. The computer system of claim 14, wherein the processorfurther executes the program instructions to: determine whether thechatbot response contains a question regarding the one or more of theresponses activating the chatbot response trigger; and receive responsesto the question regarding the one or more of the responses from the oneor more employees providing the one or more of the responses activatingthe chatbot response trigger in response to determining that the chatbotresponse contains a question regarding the one or more of the responsesactivating the chatbot response trigger.
 16. The computer system ofclaim 15, wherein the processor further executes the programinstructions to: store all employee responses as the dialog between thechatbot manager and the plurality of employees regarding the currentcorporate topic in a dialog database, wherein the dialog includes thequestion, all of the employee responses, dialog identifier, dialogtimestamps, and dialog context.
 17. The computer system of claim 12,wherein the processor further executes the program instructions to:determine whether a follow up question regarding the current corporatetopic was received from the human resource agent after reviewing therelevant information and the insights in the dashboard; and send thefollow up question via a network to a plurality of personal corporatesurvey chatbots corresponding to the plurality of employees in responseto determining that a follow up question regarding the current corporatetopic was received from the human resource agent after reviewing therelevant information and the insights in the dashboard.
 18. The computersystem of claim 12, wherein the processor further executes the programinstructions to: perform, using the chatbot manager, a set of actionsteps automatically based on the relevant information and the insightsby connecting to and controlling a set of other systems via a set ofdefined application programming interfaces.
 19. The computer system ofclaim 12, wherein the relevant information is at least one of employeemental state, employee work engagement, employee concerns, and employeework environment issues related to the current corporate topic.
 20. Thecomputer system of claim 12, wherein the insights are at least one ofdescription of an issue, root cause of the issue, and possible solutionsto the issue.
 21. The computer system of claim 12, wherein the dashboardis a graphical user interface that allows the human resource agent toquickly identify any issues needing to be addressed along with anypossible solutions.
 22. The computer system of claim 12, wherein thehuman resource agent is a software program.
 23. A computer programproduct for analyzing chatbot/employee dialogs, the computer programproduct comprising a computer readable storage medium having programinstructions embodied therewith, the program instructions executable bya computer to cause the computer to perform a method of: performing, bythe computer, an analysis of a dialog between a chatbot manager and aplurality of employees regarding a current corporate topic using anartificial intelligence component; extracting, by the computer, relevantinformation regarding the current corporate topic from the dialog basedon the analysis; generating, by the computer, insights corresponding tothe relevant information regarding the current corporate topic using theartificial intelligence component; and displaying, by the computer, therelevant information regarding the current corporate topic and theinsights in a dashboard on a client device of a human resource agent.24. The computer program product of claim 23 further comprising:receiving, by the computer, a question regarding the current corporatetopic, along with a chatbot response trigger corresponding to thequestion, from the client device of the human resource agent via anetwork; sending, by the computer, using the chatbot manager, thequestion regarding the current corporate topic via the network to aplurality of personal corporate survey chatbots corresponding to theplurality of employees to start the dialog between the chatbot managerand the plurality of employees regarding the current corporate topic;and receiving, by the computer, using the chatbot manager, responses tothe question regarding the current corporate topic from the plurality ofemployees via the plurality of personal corporate survey chatbots overthe network.
 25. The computer program product of claim 24 furthercomprising: determining, by the computer, whether one or more of theresponses activate the chatbot response trigger corresponding to thequestion, wherein the chatbot response trigger initiates an automaticresponse by the chatbot manager when the chatbot response trigger isactivated by a particular employee response to the question regardingthe current corporate topic; and responsive to the computer determiningthat one or more of the responses activate the chatbot response triggercorresponding to the question, sending, by the computer, a chatbotresponse via the network to one or more personal corporate surveychatbots corresponding to one or more employees providing the one ormore of the responses activating the chatbot response trigger for thechatbot response.
 26. The computer program product of claim 25 furthercomprising: determining, by the computer, whether the chatbot responsecontains a question regarding the one or more of the responsesactivating the chatbot response trigger; and responsive to the computerdetermining that the chatbot response contains a question regarding theone or more of the responses activating the chatbot response trigger,receiving, by the computer, responses to the question regarding the oneor more of the responses from the one or more employees providing theone or more of the responses activating the chatbot response trigger.27. The computer program product of claim 26 further comprising:storing, by the computer, all employee responses as the dialog betweenthe chatbot manager and the plurality of employees regarding the currentcorporate topic in a dialog database, wherein the dialog includes thequestion, all of the employee responses, dialog identifier, dialogtimestamps, and dialog context.
 28. The computer program product ofclaim 23 further comprising: determining, by the computer, whether afollow up question regarding the current corporate topic was receivedfrom the human resource agent after reviewing the relevant informationand the insights in the dashboard; and responsive to the computerdetermining that a follow up question regarding the current corporatetopic was received from the human resource agent after reviewing therelevant information and the insights in the dashboard, sending, by thecomputer, the follow up question via a network to a plurality ofpersonal corporate survey chatbots corresponding to the plurality ofemployees.
 29. The computer program product of claim 23 furthercomprising: performing, by the computer, using the chatbot manager, aset of action steps automatically based on the relevant information andthe insights by connecting to and controlling a set of other systems viaa set of defined application programming interfaces.
 30. The computerprogram product of claim 23, wherein the relevant information is atleast one of employee mental state, employee work engagement, employeeconcerns, and employee work environment issues related to the currentcorporate topic.
 31. The computer program product of claim 23, whereinthe insights are at least one of description of an issue, root cause ofthe issue, and possible solutions to the issue.
 32. The computer programproduct of claim 23, wherein the dashboard is a graphical user interfacethat allows the human resource agent to quickly identify any issuesneeding to be addressed along with any possible solutions.
 33. Thecomputer program product of claim 23, wherein the human resource agentis a software program.
 34. A method for performing action steps based onchatbot/employee dialog analysis, the method comprising: performing ananalysis of a dialog between a chatbot manager and a plurality ofemployees regarding a current corporate topic using an artificialintelligence component; extracting relevant information regarding thecurrent corporate topic from the dialog based on the analysis;generating insights corresponding to the relevant information regardingthe current corporate topic using the artificial intelligence component;and performing a set of action steps controlling a set of systemsautomatically via a set of defined application programming interfacesbased on the relevant information and the insights.